• January 07, 2016

    Director Wang Speaks to National UTC Institution Georgia Tech about Big Data and Smart Cities

    GT2

    This past August, PacTrans Director and University of Washington professor of Civil and Environmental Engineering, Dr. Yinhai Wang, traveled to Georgia Institute of Technology (Georgia Tech) to present at a seminar title, “Big-Data-Driven Transportation Decision Making in the Smart Cities Context.” Georgia Tech is a member of the National Center for Sustainable Transportation, a National University Transportation Center, under the direction of UC Davis.

    “Transportation involves human, infrastructure, vehicle, and environmental interactions and is therefore a very complicated system,” says Dr. Wang, “Transportation activities are found affecting public health, air quality, sustainability, etc., and thus tie to everyone’s daily life and are critical for achieving goals of Smart Cities.”

    He went on to observe that transportation has typically been studied through classical methods, with typically assumptions (the ideal), limited data support, and poor computing resources. He challenged that while the theories developed through these efforts provide valuable insights in understanding transportation-related issues, they are often ineffective in large-scale transportation system analysis with massive amount of data from various sources.

    He elaborated on recent advances in sensing, networking, and computing technologies. These new assets are likely to bring in new opportunities to understand transportation systems better and address those critical transportation issues in a faster, more accountable, and more cost-effective way. To take advantage of these big data, a new theoretical framework and its supporting platform are clearly needed to integrate the quickly growing massive amount of data, typically from numerous sources of varying spatial and temporal characteristics, into the large-scale transportation problem solving and decision making processes.

    Dr. Wang shared his vision and pilot research on extracting transportation big data streams from the smart cities sensor networks and demonstrated the values of these data in large-scale system analysis and decision support through an online regional-map-based data platform named Digital Roadway Interactive Visualization and Evaluation Network (DRIVE Net).